Turns your trees into tables (ie. reads ROOT TTrees, writes summary Pandas DataFrames)
fast-carpenter can:
- Be controlled using YAML-based config files
- Define new variables
- Cut out events or define phase-space "regions"
- Produce histograms stored as CSV files using multiple weighting schemes
- Make use of user-defined stages to manipulate the data
- uproot: to load ROOT Trees into memory as numpy arrays
- fast-flow: to manage the processing config files
- fast-curator: to orchestrate the lists of datasets to be processed
A tool from the FAST-HEP collaboration.
Visit the documentation <https://fasthep-carpenter.readthedocs.io/>
_ for full details.
This package is compatible with Python >= 3.10
Install the package and dependencies
pip install .[dev]
Install the Graphviz exectuable. This can be installed via conda
conda install python-graphviz
Install test dependencies
pip install .[test]
Download test files via the FAST-HEP CLI
pip install "fasthep[dev]"
fasthep download --json tests/data/remote_data.json --destination tests/data/
Run the test suite
python -m pytest